Overview
If fashion is your passion, here is your opportunity to be working with the coolest digital ecommerce team in the Middle East, serving all your fashion needs in one place!
Ounass is your one stop destination for all things luxury making it The Definitive Home of Luxury. It’s our homegrown, local, e-commerce platform catering to the Middle Eastern customers across a realm of axes such as - Fashion consisting of Womenswear, Menswear & Kidswear, Beauty, Watches, Home & Jewelry.
At Ounass, we strongly believe that our culture is what brings us together and helps us succeed. We strive to be the leading luxury technology platform in the Middle East region, making sure we’re the first choice for our customers. We’re highly customer focus driven, ensuring that both our customers and employees are the core of the business. We’re recognized for our incredibly fast 2 hours delivery services within Dubai, while also providing a fabulous and dedicated Personal Shopping service for our VIP clientele.
We fall under the umbrella of a distinguished Al Tayer Group and are based in the ever happening and multi-cultural city of Dubai, United Arab Emirates. We currently are a growing family of 500 employees spread across the globe – UAE, United Kingdom, Turkey, Portugal, Ukraine and Sri Lanka. Ounass focuses and emphasizes on having a highly diverse and inclusive team consisting of 53 different nationalities, ensuring a strong cultural foothold.
Our young, vibrant and growing team of 500 is extremely ambitious and is constantly innovating while growing the brand name and position together as a team.
The Senior Data Scientist plays a key role in the design, development, and advancement of data-driven products, analytics, and machine learning solutions. The position works closely with cross-functional teams to translate business challenges into scalable models and insights, while actively supporting team capability through knowledge sharing, coaching, and setting high standards in analytical thinking, technical quality, and communication. The role contributes to a strong data culture by encouraging collaboration, continuous improvement, and practical application of data to drive measurable business outcomes.
Responsibilities- Partner with product managers, engineers, and business stakeholders to understand objectives and translate them into analytical problem statements.
- Contribute to defining opportunities for data science within strategic initiatives, and provide input to roadmap discussions without owning the roadmap.
- Advocate for data-driven decision-making by communicating insights, constraints, and model results in clear, business-focused terms.
- Ensure that data science work is aligned with expected business outcomes and delivered with rigor, pragmatism, and speed.
- Design a range of new Data Science Products, working with business stakeholders to identify key areas of potential growth for Ounass.
Roles and Responsibilities
- Partner closely with cross-functional teams (Product, Planning & Merchandising, Growth, Engineering) to define problem statements, clarify business needs, and shape domain priorities.
- Own the end-to-end development, maintenance, and improvement roadmap of the data science models or tools within your domain (e.g., OTB forecasting, demand prediction, customer lifecycle modeling).
- Communicate model assumptions, performance, limitations, tradeoffs, and results in clear language tailored to non-technical stakeholders.
- Facilitate discussions that ensure alignment between DS outputs and business expectations.
- Translate business requirements into clear technical plans, define milestones, and maintain a transparent backlog for your domain.
- Ensure your domain’s models, tools, and analysis frameworks are robust, scalable, and aligned with expected business outcomes.
- Identify opportunities for improvements or new features within your domain and propose iteration plans accordingly.
- Lead end-to-end modeling workflows: data exploration, feature engineering, model development, evaluation, documentation, and deployment support.
- Build predictive models using statistical, ML, and experimental…
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